# Auto-generated. Do not edit!
'''
The ``metrics`` module provides fuctions that measure the distance between two elements of a domain.
For more context, see :ref:`metrics in the User Guide <metrics-user-guide>`.
For convenience, all the functions of this module are also available from :py:mod:`opendp.prelude`.
We suggest importing under the conventional name ``dp``:
.. code:: python
>>> import opendp.prelude as dp
'''
from deprecated.sphinx import deprecated # noqa: F401 (Not every file actually has deprecated functions.)
from opendp._convert import *
from opendp._lib import *
from opendp.mod import *
from opendp.typing import *
from opendp.typing import _substitute # noqa: F401
__all__ = [
"_metric_equal",
"_metric_free",
"absolute_distance",
"change_one_distance",
"discrete_distance",
"hamming_distance",
"insert_delete_distance",
"l1_distance",
"l2_distance",
"linf_distance",
"metric_debug",
"metric_distance_type",
"metric_type",
"partition_distance",
"symmetric_distance",
"user_distance"
]
def _metric_equal(
left: Metric,
right: Metric
) -> bool:
r"""Check whether two metrics are equal.
:param left: Metric to compare.
:type left: Metric
:param right: Metric to compare.
:type right: Metric
:raises TypeError: if an argument's type differs from the expected type
:raises UnknownTypeException: if a type argument fails to parse
:raises OpenDPException: packaged error from the core OpenDP library
"""
# No type arguments to standardize.
# Convert arguments to c types.
c_left = py_to_c(left, c_type=Metric, type_name="AnyMetric")
c_right = py_to_c(right, c_type=Metric, type_name="AnyMetric")
# Call library function.
lib_function = lib.opendp_metrics___metric_equal
lib_function.argtypes = [Metric, Metric]
lib_function.restype = FfiResult
output = c_to_py(unwrap(lib_function(c_left, c_right), BoolPtr))
try:
output.__opendp_dict__ = {
'__function__': '_metric_equal',
'__module__': 'metrics',
'__kwargs__': {
'left': left, 'right': right
},
}
except AttributeError: # pragma: no cover
pass
return output
def _metric_free(
this
):
r"""Internal function. Free the memory associated with `this`.
:param this:
:type this: Metric
:raises TypeError: if an argument's type differs from the expected type
:raises UnknownTypeException: if a type argument fails to parse
:raises OpenDPException: packaged error from the core OpenDP library
"""
# No type arguments to standardize.
# Convert arguments to c types.
c_this = this
# Call library function.
lib_function = lib.opendp_metrics___metric_free
lib_function.argtypes = [Metric]
lib_function.restype = FfiResult
output = c_to_py(unwrap(lib_function(c_this), ctypes.c_void_p))
try:
output.__opendp_dict__ = {
'__function__': '_metric_free',
'__module__': 'metrics',
'__kwargs__': {
'this': this
},
}
except AttributeError: # pragma: no cover
pass
return output
[docs]
def absolute_distance(
T: RuntimeTypeDescriptor
) -> Metric:
r"""Construct an instance of the `AbsoluteDistance` metric.
[absolute_distance in Rust documentation.](https://docs.rs/opendp/0.13.0/opendp/metrics/fn.absolute_distance.html)
:param T:
:type T: :py:ref:`RuntimeTypeDescriptor`
:raises TypeError: if an argument's type differs from the expected type
:raises UnknownTypeException: if a type argument fails to parse
:raises OpenDPException: packaged error from the core OpenDP library
"""
# Standardize type arguments.
T = RuntimeType.parse(type_name=T)
# Convert arguments to c types.
c_T = py_to_c(T, c_type=ctypes.c_char_p)
# Call library function.
lib_function = lib.opendp_metrics__absolute_distance
lib_function.argtypes = [ctypes.c_char_p]
lib_function.restype = FfiResult
output = c_to_py(unwrap(lib_function(c_T), Metric))
try:
output.__opendp_dict__ = {
'__function__': 'absolute_distance',
'__module__': 'metrics',
'__kwargs__': {
'T': T
},
}
except AttributeError: # pragma: no cover
pass
return output
[docs]
def change_one_distance(
) -> Metric:
r"""Construct an instance of the `ChangeOneDistance` metric.
:raises TypeError: if an argument's type differs from the expected type
:raises UnknownTypeException: if a type argument fails to parse
:raises OpenDPException: packaged error from the core OpenDP library
"""
# No type arguments to standardize.
# No arguments to convert to c types.
# Call library function.
lib_function = lib.opendp_metrics__change_one_distance
lib_function.argtypes = []
lib_function.restype = FfiResult
output = c_to_py(unwrap(lib_function(), Metric))
try:
output.__opendp_dict__ = {
'__function__': 'change_one_distance',
'__module__': 'metrics',
'__kwargs__': {
},
}
except AttributeError: # pragma: no cover
pass
return output
[docs]
def discrete_distance(
) -> Metric:
r"""Construct an instance of the `DiscreteDistance` metric.
:raises TypeError: if an argument's type differs from the expected type
:raises UnknownTypeException: if a type argument fails to parse
:raises OpenDPException: packaged error from the core OpenDP library
"""
# No type arguments to standardize.
# No arguments to convert to c types.
# Call library function.
lib_function = lib.opendp_metrics__discrete_distance
lib_function.argtypes = []
lib_function.restype = FfiResult
output = c_to_py(unwrap(lib_function(), Metric))
try:
output.__opendp_dict__ = {
'__function__': 'discrete_distance',
'__module__': 'metrics',
'__kwargs__': {
},
}
except AttributeError: # pragma: no cover
pass
return output
[docs]
def hamming_distance(
) -> Metric:
r"""Construct an instance of the `HammingDistance` metric.
:raises TypeError: if an argument's type differs from the expected type
:raises UnknownTypeException: if a type argument fails to parse
:raises OpenDPException: packaged error from the core OpenDP library
"""
# No type arguments to standardize.
# No arguments to convert to c types.
# Call library function.
lib_function = lib.opendp_metrics__hamming_distance
lib_function.argtypes = []
lib_function.restype = FfiResult
output = c_to_py(unwrap(lib_function(), Metric))
try:
output.__opendp_dict__ = {
'__function__': 'hamming_distance',
'__module__': 'metrics',
'__kwargs__': {
},
}
except AttributeError: # pragma: no cover
pass
return output
[docs]
def insert_delete_distance(
) -> Metric:
r"""Construct an instance of the `InsertDeleteDistance` metric.
:raises TypeError: if an argument's type differs from the expected type
:raises UnknownTypeException: if a type argument fails to parse
:raises OpenDPException: packaged error from the core OpenDP library
"""
# No type arguments to standardize.
# No arguments to convert to c types.
# Call library function.
lib_function = lib.opendp_metrics__insert_delete_distance
lib_function.argtypes = []
lib_function.restype = FfiResult
output = c_to_py(unwrap(lib_function(), Metric))
try:
output.__opendp_dict__ = {
'__function__': 'insert_delete_distance',
'__module__': 'metrics',
'__kwargs__': {
},
}
except AttributeError: # pragma: no cover
pass
return output
[docs]
def l1_distance(
T: RuntimeTypeDescriptor
) -> Metric:
r"""Construct an instance of the `L1Distance` metric.
[l1_distance in Rust documentation.](https://docs.rs/opendp/0.13.0/opendp/metrics/fn.l1_distance.html)
:param T:
:type T: :py:ref:`RuntimeTypeDescriptor`
:raises TypeError: if an argument's type differs from the expected type
:raises UnknownTypeException: if a type argument fails to parse
:raises OpenDPException: packaged error from the core OpenDP library
"""
# Standardize type arguments.
T = RuntimeType.parse(type_name=T)
# Convert arguments to c types.
c_T = py_to_c(T, c_type=ctypes.c_char_p)
# Call library function.
lib_function = lib.opendp_metrics__l1_distance
lib_function.argtypes = [ctypes.c_char_p]
lib_function.restype = FfiResult
output = c_to_py(unwrap(lib_function(c_T), Metric))
try:
output.__opendp_dict__ = {
'__function__': 'l1_distance',
'__module__': 'metrics',
'__kwargs__': {
'T': T
},
}
except AttributeError: # pragma: no cover
pass
return output
[docs]
def l2_distance(
T: RuntimeTypeDescriptor
) -> Metric:
r"""Construct an instance of the `L2Distance` metric.
[l2_distance in Rust documentation.](https://docs.rs/opendp/0.13.0/opendp/metrics/fn.l2_distance.html)
:param T:
:type T: :py:ref:`RuntimeTypeDescriptor`
:raises TypeError: if an argument's type differs from the expected type
:raises UnknownTypeException: if a type argument fails to parse
:raises OpenDPException: packaged error from the core OpenDP library
"""
# Standardize type arguments.
T = RuntimeType.parse(type_name=T)
# Convert arguments to c types.
c_T = py_to_c(T, c_type=ctypes.c_char_p)
# Call library function.
lib_function = lib.opendp_metrics__l2_distance
lib_function.argtypes = [ctypes.c_char_p]
lib_function.restype = FfiResult
output = c_to_py(unwrap(lib_function(c_T), Metric))
try:
output.__opendp_dict__ = {
'__function__': 'l2_distance',
'__module__': 'metrics',
'__kwargs__': {
'T': T
},
}
except AttributeError: # pragma: no cover
pass
return output
[docs]
def linf_distance(
T: RuntimeTypeDescriptor,
monotonic: bool = False
) -> Metric:
r"""Construct an instance of the `LInfDistance` metric.
[linf_distance in Rust documentation.](https://docs.rs/opendp/0.13.0/opendp/metrics/fn.linf_distance.html)
:param monotonic: set to true if non-monotonicity implies infinite distance
:type monotonic: bool
:param T: The type of the distance.
:type T: :py:ref:`RuntimeTypeDescriptor`
:raises TypeError: if an argument's type differs from the expected type
:raises UnknownTypeException: if a type argument fails to parse
:raises OpenDPException: packaged error from the core OpenDP library
"""
# Standardize type arguments.
T = RuntimeType.parse(type_name=T)
# Convert arguments to c types.
c_monotonic = py_to_c(monotonic, c_type=ctypes.c_bool, type_name="bool")
c_T = py_to_c(T, c_type=ctypes.c_char_p)
# Call library function.
lib_function = lib.opendp_metrics__linf_distance
lib_function.argtypes = [ctypes.c_bool, ctypes.c_char_p]
lib_function.restype = FfiResult
output = c_to_py(unwrap(lib_function(c_monotonic, c_T), Metric))
try:
output.__opendp_dict__ = {
'__function__': 'linf_distance',
'__module__': 'metrics',
'__kwargs__': {
'monotonic': monotonic, 'T': T
},
}
except AttributeError: # pragma: no cover
pass
return output
[docs]
def metric_debug(
this: Metric
) -> str:
r"""Debug a `metric`.
:param this: The metric to debug (stringify).
:type this: Metric
:raises TypeError: if an argument's type differs from the expected type
:raises UnknownTypeException: if a type argument fails to parse
:raises OpenDPException: packaged error from the core OpenDP library
"""
# No type arguments to standardize.
# Convert arguments to c types.
c_this = py_to_c(this, c_type=Metric, type_name=None)
# Call library function.
lib_function = lib.opendp_metrics__metric_debug
lib_function.argtypes = [Metric]
lib_function.restype = FfiResult
output = c_to_py(unwrap(lib_function(c_this), ctypes.c_char_p))
try:
output.__opendp_dict__ = {
'__function__': 'metric_debug',
'__module__': 'metrics',
'__kwargs__': {
'this': this
},
}
except AttributeError: # pragma: no cover
pass
return output
[docs]
def metric_distance_type(
this: Metric
) -> str:
r"""Get the distance type of a `metric`.
:param this: The metric to retrieve the distance type from.
:type this: Metric
:raises TypeError: if an argument's type differs from the expected type
:raises UnknownTypeException: if a type argument fails to parse
:raises OpenDPException: packaged error from the core OpenDP library
"""
# No type arguments to standardize.
# Convert arguments to c types.
c_this = py_to_c(this, c_type=Metric, type_name=None)
# Call library function.
lib_function = lib.opendp_metrics__metric_distance_type
lib_function.argtypes = [Metric]
lib_function.restype = FfiResult
output = c_to_py(unwrap(lib_function(c_this), ctypes.c_char_p))
try:
output.__opendp_dict__ = {
'__function__': 'metric_distance_type',
'__module__': 'metrics',
'__kwargs__': {
'this': this
},
}
except AttributeError: # pragma: no cover
pass
return output
[docs]
def metric_type(
this: Metric
) -> str:
r"""Get the type of a `metric`.
:param this: The metric to retrieve the type from.
:type this: Metric
:raises TypeError: if an argument's type differs from the expected type
:raises UnknownTypeException: if a type argument fails to parse
:raises OpenDPException: packaged error from the core OpenDP library
"""
# No type arguments to standardize.
# Convert arguments to c types.
c_this = py_to_c(this, c_type=Metric, type_name=None)
# Call library function.
lib_function = lib.opendp_metrics__metric_type
lib_function.argtypes = [Metric]
lib_function.restype = FfiResult
output = c_to_py(unwrap(lib_function(c_this), ctypes.c_char_p))
try:
output.__opendp_dict__ = {
'__function__': 'metric_type',
'__module__': 'metrics',
'__kwargs__': {
'this': this
},
}
except AttributeError: # pragma: no cover
pass
return output
[docs]
def partition_distance(
metric: Metric
) -> Metric:
r"""Construct an instance of the `PartitionDistance` metric.
[partition_distance in Rust documentation.](https://docs.rs/opendp/0.13.0/opendp/metrics/fn.partition_distance.html)
:param metric: The metric used to compute distance between partitions.
:type metric: Metric
:raises TypeError: if an argument's type differs from the expected type
:raises UnknownTypeException: if a type argument fails to parse
:raises OpenDPException: packaged error from the core OpenDP library
"""
# No type arguments to standardize.
# Convert arguments to c types.
c_metric = py_to_c(metric, c_type=Metric, type_name=None)
# Call library function.
lib_function = lib.opendp_metrics__partition_distance
lib_function.argtypes = [Metric]
lib_function.restype = FfiResult
output = c_to_py(unwrap(lib_function(c_metric), Metric))
try:
output.__opendp_dict__ = {
'__function__': 'partition_distance',
'__module__': 'metrics',
'__kwargs__': {
'metric': metric
},
}
except AttributeError: # pragma: no cover
pass
return output
[docs]
def symmetric_distance(
) -> Metric:
r"""Construct an instance of the `SymmetricDistance` metric.
:raises TypeError: if an argument's type differs from the expected type
:raises UnknownTypeException: if a type argument fails to parse
:raises OpenDPException: packaged error from the core OpenDP library
"""
# No type arguments to standardize.
# No arguments to convert to c types.
# Call library function.
lib_function = lib.opendp_metrics__symmetric_distance
lib_function.argtypes = []
lib_function.restype = FfiResult
output = c_to_py(unwrap(lib_function(), Metric))
try:
output.__opendp_dict__ = {
'__function__': 'symmetric_distance',
'__module__': 'metrics',
'__kwargs__': {
},
}
except AttributeError: # pragma: no cover
pass
return output
[docs]
def user_distance(
descriptor: str
) -> Metric:
r"""Construct a new UserDistance.
Any two instances of an UserDistance are equal if their string descriptors are equal.
Required features: `honest-but-curious`
**Why honest-but-curious?:**
Your definition of `d` must satisfy the requirements of a pseudo-metric:
1. for any $x$, $d(x, x) = 0$
2. for any $x, y$, $d(x, y) \ge 0$ (non-negativity)
3. for any $x, y$, $d(x, y) = d(y, x)$ (symmetry)
4. for any $x, y, z$, $d(x, z) \le d(x, y) + d(y, z)$ (triangle inequality)
:param descriptor: A string description of the metric.
:type descriptor: str
:raises TypeError: if an argument's type differs from the expected type
:raises UnknownTypeException: if a type argument fails to parse
:raises OpenDPException: packaged error from the core OpenDP library
"""
assert_features("honest-but-curious")
# No type arguments to standardize.
# Convert arguments to c types.
c_descriptor = py_to_c(descriptor, c_type=ctypes.c_char_p, type_name="String")
# Call library function.
lib_function = lib.opendp_metrics__user_distance
lib_function.argtypes = [ctypes.c_char_p]
lib_function.restype = FfiResult
output = c_to_py(unwrap(lib_function(c_descriptor), Metric))
try:
output.__opendp_dict__ = {
'__function__': 'user_distance',
'__module__': 'metrics',
'__kwargs__': {
'descriptor': descriptor
},
}
except AttributeError: # pragma: no cover
pass
return output
